Restaurant Data by Segment

by Dylan Chadwick4 Min Read

Restaurant data is a resource every operator should be mining, no matter their segment.

Restaurant Data —what an open-ended term! If you're a restaurant operator, you've likely encountered it by now. In practice, analyzing and applying restaurant data can seem a bit overwhelming. After all, restaurants, no matter their size, generate untold amounts of data every day, from the number of napkins they keep in stock to their average party size and sale. That's a massive amount of info!

In reality, restaurant data is a resource every operator should be mining, no matter their segment. And you don't need to be an expert with numbers or sacrifice precious time to do it. We've broken this article down into four primary restaurant segments to illustrate the significant "data generators" and how you can track that data. Since all restaurants are unique, remember that you can "mix and match" here and that these data points aren't mutually exclusive to one segment. This article should serve as a useful springboard for you in your restaurant analytics efforts!

Quick Service

As the name suggests, your primary focus here is processing orders quickly and efficiently. As such, you'll want to focus on the back-of-house operations here. Some data points to examine include: 

  • Cook times - Denotes the start and finish time of an entree; Literally, how long it to prepare.
  • Plating to Table/Counter Times - How long it takes to get the order from the kitchen back onto the floor. These are the types of data you can use to determine chokepoints and holdups in your kitchen, your literal speed of service To track this data, you'll want an automated solution, like a kitchen display system, which can track and store this data for you. By analyzing cook times and trends, you can identify peak traffic times, as well as other bottlenecks in your workflow. Additionally, a system with "expo views" that allow you to section off into different kitchen stations will help you further identify your kitchen efficacy, at a granular level.
Fast Casual

Working in the fast-casual segment, you're obviously still going to consider your BOH operations, but will also put more emphasis on your guest management efforts like how well you're blending your traffic between walk-in guests, off-premise pickup and delivery, and every other dining variation the segment has to offer.

Some additional data points to consider include:

  • Average party size - At a given moment, the number of guests you're likely to see per order. While you may not offer table service, it's still a useful metric to consider with limited seating.
  • Average order - Here's the average amount of money a guest spends per visit, data you can measure to determine your most profitable hours, shifts, seasons and entrees.

You'll need technology that can integrate with your POS so that you can gain insight into your customer's spending patterns. Remember also that with guest traffic coming from so many different areas, a KDS with capacity management features can help in streamlining this. It can "read" the existing workload in your restaurant, and use this data to create accurate pickup quotes for off-premise customers.

Casual Dining

With so much emphasis on table service in the casual dining segment, you need front and back-of-house technology to keep all your processes in order. Not only are you considering your kitchen bandwidth, but you've also got to account for your seating economy.  

Some additional data to measure in this segment include:

  • Wait times - Utilizing all the data at a given moment, like existing traffic and average turnaround times, how long will a party of a given size need to wait? Often, these are high-volume restaurants.
  • Turnaround times: This determines the figurative "life cycle" of a guest or party, from the time they order to the time they leave.
  • Seating efficiency: the actual measure of how well you're utilizing the seats in your restaurant. While a seating efficiency of 100 percent isn't likely, it's the benchmark.

While you could calculate all of these manually, a more effective option is to use a guest management tool which can automatically calculate this data, as well as present historical averages to compare against current data. You can measure this data to determine places or times in your workflow when traffic spikes, data which can help inform your staffing efforts. Depending on your restaurant, you may also want something with waitlist and reservation capabilities. 

Fine Dining

At this segment, you've got to have every process in your restaurant running at optimal level. Here, you're not dealing with so much walk-up traffic, as much as reservations and waitlisting. In this regard, capacity management features in your BOH - those that can consider average turnaround times, and provide real-time order statuses - will help pace your orders, keeping food fresh and hot for the ideal guest experience. Ideally, you want waitlist technology that can integrate with your BOH when taking in reservations to prevent you from overbooking.

Catch-All's
  • Inventory Management - No matter your segment, you need to stay on top of the finite resources in your restaurant. While you could keep a paper-and-pencil accounting of everything you've got, we wouldn't recommend it! Look for something automated, and which can alert you when something gets low, so you can stay on top of your materials.
  • Customer Data - Guests are the lifeblood of any restaurant, no matter the market. Look for ways to store customer data, like order histories or food allergies so that you can market to them more effectively. Consider creating a loyalty program to incentivize them with future visits.

Ultimately, your restaurant will create data, no matter what. Those willing to track and analyze that data, and employ an automated solution to help, will build more a more efficient, more profitable operation.

Dylan Chadwick

@qsrautomations | LinkedIn | Website

Dylan Chadwick is a Content Marketing Specialist at QSR Automations. He graduated from Brigham Young University with an English degree and journalism focus and loves to write about technology.

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